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Latent Space Translation via Semantic Alignment
Different neural models often exhibit similar latent spaces when exposed to semantically similar data; however, this inherent …
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Latent Space Translation via Semantic Alignment
Leveraging sparse and shared feature activations for disentangled representation learning
Recovering the latent factors of variation of high dimensional data has so far focused on simple synthetic settings. Mostly building on …
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Leveraging sparse and shared feature activations for disentangled representation learning
AVEN-GR: Attribute Value Extraction and Normalization using product GRaphs
Getting a good understanding of the user intent is vital for e-commerce applications to surface the right product to a given customer …
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AVEN-GR: Attribute Value Extraction and Normalization using product GRaphs
Mitigating the Burden of Redundant Datasets via Batch-Wise Unique Samples and Frequency-Aware Losses
Datasets used to train deep learning models in industrial settings often exhibit skewed distributions with some samples repeated a …
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Mitigating the Burden of Redundant Datasets via Batch-Wise Unique Samples and Frequency-Aware Losses
Fauno - The Italian Large Language Model that will leave you senza parole!
This paper presents Fauno, the first and largest open-source Italian conversational Large Language Model (LLM). Our goal with Fauno is …
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Fauno - The Italian Large Language Model that will leave you senza parole!
Adversarial Permutation Invariant Training for Universal Sound Separation
Universal sound separation consists of separating mixes with arbitrary sounds of different types, and permutation invariant training …
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Adversarial Permutation Invariant Training for Universal Sound Separation
Accelerating Transformer Inference for Translation via Parallel Decoding
Autoregressive decoding limits the efficiency of transformers for Machine Translation (MT). The community proposed specific network …
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Accelerating Transformer Inference for Translation via Parallel Decoding
Multimodal Neural Databases
The rise in loosely-structured data available through text, images, and other modalities has called for new ways of querying them. …
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Multimodal Neural Databases
Relative representations enable zero-shot latent space communication
Neural networks embed the geometric structure of a data manifold lying in a high-dimensional space into latent representations. …
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Relative representations enable zero-shot latent space communication
Latent Autoregressive Source Separation
Autoregressive models have achieved impressive results over a wide range of domains in terms of generation quality and downstream task …
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Latent Autoregressive Source Separation